Classification of Tweets Using Natural Language Processing from Twitter API Data
P. Nagaraj, Venkatkumar Muneeswaran, M Ritika, V. Saranya, N Gayathri, P V Gowthami · 2023
With coarse, diverse, and likely unfiltered general knowledge and the unrealistic state of manually tagging a significant number of tweets using coaching classifiers, job sentiment analysis classification Obtaining information for coaching children becomes a major challenge. In this article, we present a solution to axiomatically retrieve labeled, filtered, large-scale coaching job information from Twitter that can be used as input to a support vector machine classifier. There are various implements and methods for performing sentiment detection and analysis on the side of supervised machine learning algorithms. This algorithm performs categorization on a prey collection instructed on coaching job information. Here, we utilized support vector machines (SVMs) for sentiment analysis on Weka. SVM is a well-known supervised machine-learning technique for detecting ground polarity.